Python for Data Analysis & Visualization

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Malvik Vaghadia,Pathfinder Analytics

9:59:56

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01 - Course Welcome & Set Up

001 Course Overview.mp4

02:17

002 Udemy 101.html

003 Python Overview.mp4

04:40

004 Anaconda Distribution Installation.mp4

04:19

005 Jupyter Notebook 101.mp4

09:19

006 Jupyter Notebook - Adding Comments in Cells.mp4

00:56

007 Course Resources - Important!.mp4

01:49

007 Course-Resurces-Python-for-Data-Analysis-and-Visualization.zip

02 - Objects, Variables and Data Types

001 Objects and Variables Overview.mp4

09:56

002 Numbers.mp4

06:22

003 Integer Variables.html

004 Coding Exercise Solution.html

005 Float Variables.html

006 Coding Exercise Solution.html

007 Strings.mp4

05:56

008 Print Formatting with Strings.html

009 Coding Exercise Solution.html

010 String Operations.mp4

07:48

011 String Indexing and Slicing Quiz.html

012 String Methods and Properties.mp4

08:09

013 String Methods.html

014 Coding Exercise Solution.html

015 String Concatenation and Formatting.mp4

03:09

016 Lists.mp4

16:02

017 Lists.html

018 Coding Exercise Solution.html

019 Lists.html

020 Coding Exercise Solution.html

021 Dictionaries.mp4

09:32

022 Dictionaries.html

023 Coding Exercise Solution.html

024 Tuples and Sets.mp4

07:35

025 Tuples and Sets.html

026 Coding Exercise Solution.html

027 Booleans.mp4

01:01

028 Key Words in Python.html

029 Data Types.html

03 - Control Flow and Loops

001 Python Operators.mp4

08:06

002 Control Flow.mp4

12:33

003 Control Flow.html

004 Coding Exercise Solution.html

005 For Loops.mp4

12:45

006 For Loops (continued).mp4

06:13

007 For Loops.html

008 Coding Exercise Solution.html

009 For Loops.html

010 Coding Exercise Solution.html

011 While Loops.mp4

03:03

012 Break, Continue and Pass Statements.mp4

04:41

013 List Comprehension.mp4

03:52

014 List Comprehension.html

015 Coding Exercise Solution.html

016 IN and NOT IN.mp4

03:12

04 - Functions

001 Built-In Functions.mp4

14:55

002 Built-In Functions.html

003 Coding Exercise Solution.html

004 User Defined Functions.mp4

06:09

005 User Defined Functions - Examples.mp4

08:59

006 User Defined Functions.html

007 Coding Exercise Solution.html

008 User Defined Functions.html

009 Coding Exercise Solution.html

010 Arguments and Keyword Arguments.mp4

13:37

011 Map and Filter.mp4

07:29

012 Lambda Functions.mp4

05:05

013 Lambda Functions.html

014 Coding Exercise Solution.html

015 Errors and Exception Handling.mp4

04:37

05 - Challenge Section - Core Python

001 Challenge Questions Overview.mp4

06:00

002 Solutions Walkthrough.mp4

09:19

003 Corection Solutions.html

06 - Modules, Packages and Libraries

001 Built-In Modules.mp4

03:29

002 External Libraries.mp4

02:46

07 - NumPy

001 NumPy Overview.mp4

10:44

002 Array Slicing and Indexing.mp4

08:34

003 Array Manipulation Functions.mp4

09:16

004 Additional Array Creation Functions.mp4

07:01

005 Array Arithmetic and Mathematical Functions.mp4

10:35

006 IO Functions in NumPy.mp4

08:29

08 - Challenge Section - NumPy

001 Challenge Questions.mp4

02:59

002 Challenge Solutions.mp4

04:56

09 - Pandas

001 Pandas Overview.mp4

02:17

002 Introduction to Series.mp4

09:02

003 Introduction to DataFrames.mp4

12:32

004 Selecting Data 1.mp4

11:14

005 Selecting Data 2.mp4

01:48

006 Data Manipulation 1.mp4

16:19

007 Data Manipulation 2.mp4

09:28

008 Data Aggregation and Grouping.mp4

12:29

009 Data Cleansing.mp4

08:03

010 Combining DataFrames.mp4

11:48

011 Windowing Operations.mp4

05:51

10 - Challenge Section - Pandas

001 Challenge Questions - TfL Dataset.mp4

01:22

002 Solutions Walkthrough.mp4

04:44

003 Challenge Questions - Employees Dataset.mp4

01:08

004 Solutions Walkthrough.mp4

07:56

11 - Data Sources

001 Excel and CSV.mp4

03:45

002 HTML.mp4

02:52

003 Databases.mp4

04:38

004 Pandas Input and Output Methods.mp4

00:46

12 - Matplotlib

001 Matplotlib Overview.mp4

01:54

002 Choosing the Right Chart Type.mp4

01:54

003 Creating a Plot Area 1.mp4

12:40

004 Creating a Plot Area 2.mp4

06:44

005 Bar Plots.mp4

15:01

006 Line Plots.mp4

06:37

007 FIFA 21 Player Dataset.html

008 Scatter Plots.mp4

04:56

009 Histograms.mp4

03:36

010 Box Plots and Violin Plots.mp4

06:41

011 Style and Presentation.mp4

06:29

012 Additional Resources and Cheat Sheets.mp4

02:06

13 - Challenge Section - Matplotlib

001 Challenge Questions Overview.mp4

02:34

002 Solutions Walkthrough.mp4

07:02

14 - Seaborn

001 Seaborn Overview.mp4

01:19

002 Categorical Plots.mp4

15:26

003 Relational Plots.mp4

10:53

004 Distribution Plots.mp4

11:37

005 Regression Plots.mp4

06:28

006 Matrix Plots.mp4

06:01

007 Multi Plot Grids.mp4

15:37

008 Style and Presentation.mp4

04:43

15 - Challenge Section - Seaborn

001 Challenge Questions Overview.mp4

01:23

002 Solutions Walkthrough.mp4

05:44

16 - Plotly Express

001 Plotly Express Overview.mp4

03:02

002 Interactive Charts in Plotly Express.mp4

08:07

003 3D Charts.mp4

04:06

004 BONUS Further Learning.mp4

01:00

005 BONUS Further Learning Resources.html

17 - Keep learning with me

001 BONUS Check out my other courses.html

Description

Master the main data analysis and visualization libraries in Python: Numpy, Pandas, Matplotlib, Seaborn, Plotly + more

What You'll Learn?

Python, we will be using Python3 in this course
Data Analysis Libraries in Python such as NumPy and Pandas
Data Visualization Libraries in Python such as Matplotlib and Seaborn
How to analyse data
Data Visualization
Jupyter Notebooks IDE / Anaconda Distribution

Who is this for?

Python developers curious about the data analysis libraries

Python developers curious about the data visualization libraries

Anyone interested in learning Python

Data Analysts

Anyone working with data

What You Need to Know?

No prior knowledge required

More details

Description
Learn one of the most in demand programming languages in the world and master the most important libraries when it comes to analysing and visualizing data.
This course can be split into 3 key areas:
The first area of the course focuses on core Python3 and teaches you the essentials you need to be able to master the libraries taught in this course
The second area focuses on analysing and manipulating data. You will learn how to master both NumPy and Pandas
For the final part of the course you learn how to display our data in the form of interesting charts using Matplotlib,Â Seaborn and Plotly Express
You will be using Jupyter Notebooks as part of the Anaconda Distribution. Jupyter is the most popular Python IDE available.
The course is packed with lectures, code-along videos, coding exercises and quizzes.
On top of that there are numerous dedicated challenge sections that utilize interesting datasets to enable you to make the most out of these external libraries.
There should be more than enough to keep you engaged and learning! As an added bonus you will also have lifetime access to all the lectures as well as lots of downloadable course resources consisting of detailed Notebooks.
The aim of this course is to make you proficient at using Python and the data analysis and visualization libraries.
This course is suitable for students of all levels and it doesnâ€™t matter what operating system you use.
Curriculum summary:
Set Up & Installation
Core Python
Python Objects, Variables and Data Types
Control Flow and Loops
Functions
External Libraries
Data Analysis Libraries
NumPy
Pandas
Connecting to different Data Sources
Visualization Libraries
Matplotlib
Seaborn
Plotly Express
4 dedicated Challenge Sections!
Who this course is for:
Python developers curious about the data analysis libraries
Python developers curious about the data visualization libraries
Anyone interested in learning Python
Data Analysts
Anyone working with data

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Python

Malvik Vaghadia

Instructor's Courses

Malvik is an Instructor specialising in Data Analytics and Visualization.He has spent 10+ years working for and consulting a number of publicly listed / unlisted companies as a Data and BI specialist. Over the course of his career Malvik has developed a skillset in data engineering, data analytics and visualisation, with expertise across a number of technologies and programming languages including SQL, Python and R. He has worked extensively with a number of leading software platforms including Azure, Hadoop, Spark, Databricks, MongoDB, Oracle, MySQL, MS SQL Server, Qlik and Microsoft Power Platforms.

Pathfinder Analytics

Instructor's Courses

Pathfinder Analytics excels in delivering high quality online courses in Data Analysis, Data Engineering and Business Intelligence.With a focus on providing practical, job-ready skills, Pathfinder Analytics has empowered students around the world with in demand data skills. Explore our offerings to enhance your expertise, master essential tools, and advance your career in data.

Udemy

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